Several readers have inquired about the seasonality factor when it comes to equities, which I mentioned last week (Tactical Shift: Reducing Cash).

Let’s take a quick look at the history off the seasonal advantages. “The Best Six Months of the Year” was first described by Yale Hirsch in Stock Traders Almanac decades ago. The historical chart below via Investech Research reveals the surprising degree of seasonality for investors, going back 50 years.

Here are the specifics of seasonality: Imagine we start with two $10,000 accounts, and use them to make investments in an S&P 500 Index fund. One account invests in one 6-month period, the other invests in the remaining 6-month period. Account A is invested from November 1st through April 30th each year, while Account B is invested from May 1st through October 31st.

Here are the numbers:

• Account A portfolio grew from $10,000 to over $438,967. That is a 42-fold increase.

• Account B portfolio barely doubled to $22,659.

By selecting the seasonally strong period from November through April, you capture 97.1% of the available performance over the past 52 years. (Note the November-April seasonality fared poorly in 2007 and 2008).

Please use the comments to demonstrate your own ignorance, unfamiliarity with empirical data and lack of respect for scientific knowledge. Be sure to create straw men and argue against things I have neither said nor implied. If you could repeat previously discredited memes or steer the conversation into irrelevant, off topic discussions, it would be appreciated. Lastly, kindly forgo all civility in your discourse . . . you are, after all, anonymous.

30 Responses to “A Tale of 2 Seasonal Investors”

I think that the other caveat is that by simple data-mining, there has to be some 6 month period that can be chosen over the course of X years that will outperform another 6 month period. (Simple example, why Nov 1 and not start Oct. 28? etc.) By mining through each 6-month period comparison, we can find one that is the best. The questions investors need to ponder is whether there is predictive value in that comparison, and how robust is the model. Without some underlying logic to the seasonality patterns (which some seasonal models have) you might be misled.

~~~

BR: Simple data mining will no pick up a 97.5% versus 2.5% differential.

A century ago, when most of the population still lived on farms, a theory held that farmers drew down credit to plant crops … and paid it back upon selling crops at harvest, thus reliquifying the financial system during the winter and early spring.

Why this pattern would persist in the post-industrial age is a bit of a mystery, though.

@noahmckinnon — even as farm size and output have grown, agriculture’s share of GDP has declined from a majority to a few percent — hardly enough to drive such a pronounced seasonal pattern, one would think.

The 4-year presidential cycle can be rationalized in terms of politically-driven economic manipulation. But Nov-Apr seasonality is a real puzzler.

Of course the deer rut and opening of hunting season correspond nicely as well. I wonder could deer and human testosterone levels be linked with the seasons. No matter, I’m looking forward to a productive hunting season both in equities and deer. For those of you living in the city; deer are animals you hunt and they live in the forest and the forest is a large grouping of trees and trees are…

Barry — i think you meant arithmetic not algorithmic. but we got the idea.

One thing that bothered me about buy-sell-buy strategies is where does the money for the taxes come from?

Every year you have to pay short-term capital gains taxes on the profits, if you take it out of the strategy fund, you can’t do as well as this. and in some years where there is beaucoup gains you are going to have a hefty tax bill.

I think an earlier poster had the right question… where the no-load low-cost mutual fund that is following this strategy?

Hunting season mere correlation? I thought that what was all that was going on down there, the Street jungle I inhabited for about 2 decades or so. I got to eat a part of what I killed, mostly less-intelligent members of my own species. But then the birds told me about species awareness. I took the pledge and I’m on the hunt for the smarter members who have moved on.

And, suppose one had invested $10,000 in the S&P 500 Index on January 3, 1960 and did no trading at all? According to a calculator on IFA’s website, the ending value as of Sept 30, 2011 would be $872,202. That appears to include re-invested dividends, but is not adjusted for inflation and does not include taxes on dividends. The total annual return is approximately 9 percent. http://www.ifa.com/portfolios/PortReturnCalc/index.aspx

It strikes me that even the seasonal investor is wasting his time, energy and money if his total return is only $438,967. And, this figure is apparently not adjusted for the trading fees or taxes on capital gains, the latter necessarily at ordinary tax rates since the holding period is less than 6 months. Granted, investor A could have parked his cash in a money market fund for the months May through October, but I seriously doubt this would compensate for the trading commissions (there were no discount brokers in the 1960′s) and taxes on capital gains.

The most I could say for Investor A is that he (or she) is the Lesser Loser.

Financial Times refered to “Sell in May” in 1964 and the pattern shows up around the globe. So, sceptics forget about data mining.

More interesting question remains howcome this pattern continues to be so strong. My current personal believe remains that this pattern is connected to a cycle in investors’ optimism as I described in http://papers.ssrn.com/sol3/papers.cfm?abstract_id=643583. I welcome other suggestions.

Barry,
I believe this may well be a mere data mining.
To prove the point, I just made several simple simulations of the random price in excel. I assumed that each month the price follows a lognormal distribution with a fixed mean and standard deviation. So there was no any seasonality in the data by construction. The distribution of returns doesn’t change from month to month. The simulation is done over 50 years (600 months).
Now, there is often a staggering difference in investment results for the strategies that invest only in the first 6 months of the year and the last six months of the year. I didn’t make many simulations, but even in the first few the results differed as much as +2500% and -85% (over 50 years), for instance. So, your assertion that the probability of such a high difference in investment results between the two accounts is very low may well be simply wrong. Actually, this may be a question to a person with a good knowledge of statistics (I don’t) – what’s the statistical probability of the above mentioned difference?

Say Hello

About Barry Ritholtz

Ritholtz has been observing capital markets with a critical eye for 20 years. With a background in math & sciences and a law school degree, he is not your typical Wall St. persona. He left Law for Finance, working as a trader, researcher and strategist before graduating to asset managementRead More...

Quote of the Day

"Misers aren't fun to live with, but they make wonderful ancestors." -David Brenner

Sign Up For My Newsletter

Get subscriber only insights and news delivered by Barry every two weeks.